Car noise verification and applications

Krishnamurthy, Nitish; Hansen, John H. L.

doi:10.1007/s10772-013-9215-3

Cited by 7 publications

(5 citation statements)

References 31 publications

(34 reference statements)

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“…For our evaluations, we focus on an automotive noise scenario that is typical for ICC applications. We employ speech signals from the Keele speech database [7] and automotive noise from the UTD-CAR-NOISE database [8]. The signals are downsampled to a sampling rate of f s = 16 kHz.…”

Section: Experiments and Resultsmentioning

confidence: 99%

Low-Complexity Pitch Estimation Based on Phase Differences Between Low-Resolution Spectra

Graf¹,

Herbig²,

Buck³

et al. 2017

Interspeech 2017

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Detection of voiced speech and estimation of the pitch frequency are important tasks for many speech processing algorithms. Pitch information can be used, e.g., to reconstruct voiced speech corrupted by noise. In automotive environments, driving noise especially affects voiced speech portions in the lower frequencies. Pitch estimation is therefore important, e.g., for in-car-communication systems. Such systems amplify the driver's voice and allow for convenient conversations with backseat passengers. Low latency is required for this application, which requires the use of short window lengths and short frame shifts between consecutive frames. Conventional pitch estimation techniques, however, rely on long windows that exceed the pitch period of human speech. In particular, male speakers' low pitch frequencies are difficult to resolve. In this publication, we introduce a technique that approaches pitch estimation from a different perspective. The pitch information is extracted based on phase differences between multiple low-resolution spectra instead of a single long window. The technique benefits from the high temporal resolution provided by the short frame shift and is capable to deal with the low spectral resolution caused by short window lengths. Using the new approach, even very low pitch frequencies can be estimated very efficiently.

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Section: Experiments and Resultsmentioning

confidence: 99%

Low-Complexity Pitch Estimation Based on Phase Differences Between Low-Resolution Spectra

Graf¹,

Herbig²,

Buck³

et al. 2017

Interspeech 2017

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“…In [84], N. Krishnamurthy et al presents a new area of research called audio-based vehicle verification, a field that can be useful within automotive digital forensics. Their work experiments on vehicle sound to verify whether a particular sound sample can be mapped to a specific vehicle.…”

Section: B Categorization Of Papersmentioning

confidence: 99%

A Systematic Literature Review on Automotive Digital Forensics: Challenges, Technical Solutions and Data Collection

Strandberg

Nowdehi

Olovsson

2023

IEEE Trans. Intell. Veh.

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A modern vehicle has a complex internal architecture and is wirelessly connected to the Internet, other vehicles, and the infrastructure. The risk of cyber attacks and other criminal incidents along with recent road accidents caused by autonomous vehicles calls for more research on automotive digital forensics. Failures in automated driving functions can be caused by hardware and software failures and cyber security issues. Thus, it is imperative to be able to determine and investigate the cause of these failures, something which requires trustable data. However, automotive digital forensics is a relatively new field for the automotive where most existing self-monitoring and diagnostic systems in vehicles only monitor safety-related events. To the best of our knowledge, our work is the first systematic literature review on the current research within this field. We identify and assess over 300 papers published between 2006 -2021 and further map the relevant papers to different categories based on identified focus areas to give a comprehensive overview of the forensics field and the related research activities. Moreover, we identify forensically relevant data from the literature, link the data to categories, and further map them to required security properties and potential stakeholders. Our categorization makes it easy for practitioners and researchers to quickly find relevant work within a particular sub-field of digital forensics. We believe our contributions can guide digital forensic investigations in automotive and similar areas, such as cyber-physical systems and smart cities, facilitate further research, and serve as a guideline for engineers implementing forensics mechanisms.

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“…Modern technological solutions that meet the needs of users are not always appropriate from the point of view of environmental protection. In order to prevent solutions that are unfavorable for the customer and harmful to the environment, it is necessary to tighten environmental standards based on the greater accuracy of vehicle identification [1]. In this context, it should be recognized that noise pollution has become a source of social tension related to economic development, on the one hand, and quality of life on the other.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, vehicle-specific noises include, among other examples, an air conditioning system and car horns. A large portion of such noises changes between vehicles [1]. Another researcher [17] showed a significant disease burden caused by environmental noise, stressing that noise is a public health problem.…”

Section: Introductionmentioning

confidence: 99%

“…According to Ibarra et al [22], new vehicles may not yet be characterized in terms of noise emission. [1] demonstrated that road characteristics are a significant factor effecting the noise levels of a vehicle, and that road surface characteristics may change the noise levels of the vehicle (e.g., asphalt vs. concrete, smooth vs. cracks or holes). Hence, passenger cars generate noise in various forms, and this noise may be generated by various components of the vehicle.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of Noise Levels in Typical Passenger Cars

et al. 2023

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Passenger cars differ in their levels of emitted noise and mileage, which can have a negative impact on the environment and humans. This was confirmed by the results of this study on the noise levels generated by passenger cars that have the same parameters, or are of one type. The loudest place in the tested vehicles turned out to be the combustion engine compartment, with the average noise level exceeding 90 dB and exhibiting a noticeable, significant increase alongside an increase in the mileage of the vehicles. This value of noise intensity is classified as dangerous for the human body. As a result of the conducted tests, it can be concluded that an engine cover is an important element in damping the sounds emitted by an internal combustion engine after the use of an aluminum heat shield to increase noise absorption. In the future, the environmental problem of noise emission from cars can be solved by encouraging the use of quieter, electric vehicles.

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Car noise verification and applications

Cited by 7 publications

References 31 publications

Low-Complexity Pitch Estimation Based on Phase Differences Between Low-Resolution Spectra

Low-Complexity Pitch Estimation Based on Phase Differences Between Low-Resolution Spectra

A Systematic Literature Review on Automotive Digital Forensics: Challenges, Technical Solutions and Data Collection

Analysis of Noise Levels in Typical Passenger Cars

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